Detection of Staphylococcus Isolates and Their Antimicrobial Resistance Profiles and Virulence Genes from Subclinical Mastitis Cattle Milk Using MALDI-TOF MS, PCR and Sequencing in Free State Province, South Africa.
Ntelekwane George KhasapaneMyburgh KoosSebolelo J NkhebenyaneZamantungwa Thobeka Happiness KhumaloTsepo RamatlaOriel Matlhahane Molifi ThekisoePublished in: Animals : an open access journal from MDPI (2024)
Staphylococcus species are amongst the bacteria that cause bovine mastitis worldwide, whereby they produce a wide range of protein toxins, virulence factors, and antimicrobial-resistant properties which are enhancing the pathogenicity of these organisms. This study aimed to detect Staphylococcus spp. from the milk of cattle with subclinical mastitis using MALDI-TOF MS and 16S rRNA PCR as well as screening for antimicrobial resistance (AMR) and virulence genes. Our results uncovered that from 166 sampled cows, only 33.13% had subclinical mastitis after initial screening, while the quarter-level prevalence was 54%. Of the 50 cultured bacterial isolates, MALDI-TOF MS and 16S rRNA PCR assay and sequencing identified S. aureus as the dominant bacteria by 76%. Furthermore, an AMR susceptibility test showed that 86% of the isolates were resistant to penicillin, followed by ciprofloxacin (80%) and cefoxitin (52%). Antimicrobial resistance and virulence genes showed that 16% of the isolates carried the mecA gene, while 52% of the isolates carried the Lg G -binding region gene, followed by coa (42%), spa (40%), hla (38%), and hlb (38%), whereas sea and bap genes were detected in 10% and 2% of the isolates, respectively. The occurrence of virulence factors and antimicrobial resistance profiles highlights the need for appropriate strategies to control the spread of these pathogens.
Keyphrases
- antimicrobial resistance
- genome wide
- genetic diversity
- genome wide identification
- staphylococcus aureus
- south africa
- biofilm formation
- mass spectrometry
- pseudomonas aeruginosa
- real time pcr
- bioinformatics analysis
- single cell
- escherichia coli
- risk assessment
- transcription factor
- high throughput
- cystic fibrosis
- gram negative
- quantum dots
- candida albicans
- sensitive detection
- antiretroviral therapy